GLM 4.1V 9B Thinking

GLM-4.1V-9B-Thinking is an open-source Vision-Language Model (VLM) jointly released by Zhipu AI and Tsinghua University’s KEG Lab, specifically designed to handle complex multimodal cognitive tasks. Built upon the GLM-4-9B-0414 base model, it integrates Chain-of-Thought (CoT) reasoning and employs reinforcement learning strategies, significantly enhancing its cross-modal reasoning capabilities and stability. As a lightweight model with 9B parameters, it strikes an optimal balance between deployment efficiency and performance. Across 28 authoritative benchmark evaluations, it matches or surpasses the performance of the 72B-parameter Qwen-2.5-VL-72B in 18 metrics. The model excels in tasks such as image-text understanding, mathematical and scientific reasoning, and video comprehension, while also supporting 4K-resolution images and arbitrary aspect ratios.